When reading a text, in particular in a foreign language, one often encounters unknown words or expressions. In such a situation, a traditional approach consists in looking up each of the unknown words or expressions in a dictionary to obtain a translation or a definition thereof.
Such an approach has limitations since many words have several meanings. Accordingly, when looking up a word or an expression in a dictionary, several translations or definitions are provided and it is necessary to choose the right one.
For the sake of illustration, the English word “please” can have different meanings: the definition of this word in the expression “Please, could you help me?” is not the same as in the expression “Do as you please”.
Similarly, it may be difficult for someone to form groups of words linguistically linked in sentences, to improve understanding of the sentence, that is to say to detect when a word is part of a larger group of words, giving it a specific meaning.
It is difficult to describe precisely the ability humans have to group words together and chunk sentences in cohesive segments, even when those segments are not “continuous”.
For example, the word “belong” bears different meanings in the expressions “I belong to you” and “I belong there” because of the groups they belong to. Likewise, for the same reason, the verb “to rip” has different meanings in the expressions “He ripped his clothes” and “He ripped everybody off”, notably because of the phrasal verb “rip off” in which another word can be inserted.
Therefore, there is a need for an improved system providing accurate translations or precise definitions of words as well as examples of use of these words.